About: Using X-ray images and deep learning for automated detection of coronavirus disease

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About: Using X-ray images and deep learning for automated detection of coronavirus disease Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Using X-ray images and deep learning for automated detection of coronavirus disease
Creator	Asnaoui, Khalid Chawki, Youness
Source	Medline; PMC
abstract	Coronavirus is still the leading cause of death worldwide. There are a set number of COVID-19 test units accessible in emergency clinics because of the expanding cases daily. Therefore, it is important to implement an automatic detection and classification system as a speedy elective finding choice to forestall COVID-19 spreading among individuals. Medical images analysis is one of the most promising research areas, it provides facilities for diagnosis and making decisions of a number of diseases such as Coronavirus. This paper conducts a comparative study of the use of the recent deep learning models (VGG16, VGG19, DenseNet201, Inception_ResNet_V2, Inception_V3, Resnet50, and MobileNet_V2) to deal with detection and classification of coronavirus pneumonia. The experiments were conducted using chest X-ray & CT dataset of 6087 images (2780 images of bacterial pneumonia, 1493 of coronavirus, 231 of Covid19, and 1583 normal) and confusion matrices are used to evaluate model performances. Results found out that the use of inception_Resnet_V2 and Densnet201 provide better results compared to other models used in this work (92.18% accuracy for Inception-ResNetV2 and 88.09% accuracy for Densnet201). Communicated by Ramaswamy H. Sarma
has issue date	2020-05-22(xsd:dateTime)
bibo:doi	10.1080/07391102.2020.1767212
bibo:pmid	32397844
has license	no-cc
sha1sum (hex)	d49e13f4521ee47403a4ce8f6c4e1e8f4613ba62
schema:url	https://doi.org/10.1080/07391102.2020.1767212
resource representing a document's title	Using X-ray images and deep learning for automated detection of coronavirus disease
has PubMed Central identifier	PMC7256347
has PubMed identifier	32397844
schema:publication	J Biomol Struct Dyn
resource representing a document's body	covid:d49e13f4521ee47403a4ce8f6c4e1e8f4613ba62#body_text
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